Optimal Damage Detection And Prognosis Via Ultrasonic Scattering

Professor Michael Todd

Ultrasonic guided wave interrogation using piezoelectric arrays and full- eld laser ultrasonic inspection has evolved into a very active research area. This research focuses on the detection, classi cation, and prognosis of damage using elastic waves as the interrogation mechanism. The novel approach in this work is the embedding of stochastic models to account for uncertainty of model/ physical parameters, in order to derive an optimal detection process that supports predictive modeling with quanti ed uncertainty. Research is focusing on maximum likelihood estimates for detecting and localizing small scatterers in complex composite and metallic structures. Detection is accomplished using generalized likelihood testing, probabilistic imaging methodologies, and optimized data domain transformations.